Separate constrained directional enhancement filter

ABSTRACT

A method, a non-transitory computer readable medium, and a computer system is provided for encoding or decoding video data. The method may include: receiving video data comprising a chroma component and a luma component; parsing, deriving or selecting a number of presets for the chroma component in one frame, and a number of presets for the luma component in the one frame; and decoding the video data. The method may further comprise: performing a separate Constrained Directional Enhancement Filter (CDEF) process of filtering luma and chroma components independent from each other based on the number of presets for the chroma component in one frame, and the number of presets for the luma component in the one frame.

PRIORITY INFORMATION

This application claims the benefit of priority from U.S. ProvisionalApplication No. 63/040,856 filed Jun. 18, 2020, which is herebyincorporated by reference in its entirety.

FIELD

The disclosure relates generally to the field of data processing, andmore particularly to video encoding and/or decoding (e.g., by a coder, adecoder or a codec (decoder and encoder)).

BACKGROUND

AOMedia Video 1 (AV1) is an open video coding format designed for videotransmissions over the Internet. It was developed as a successor to, forexample, codec extensions in the related art.

SUMMARY

Embodiments relate to a method, system, and computer readable medium forencoding and/or decoding video data. According to one aspect, a methodfor encoding and/or decoding video data is provided. The method mayinclude receiving video data comprising a chroma component and a lumacomponent; parsing, deriving or selecting a number of presets for thechroma component in one frame, and a number of presets for the lumacomponent in the one frame; and decoding the video data, wherein themethod comprises performing a separate Constrained DirectionalEnhancement Filter (CDEF) process of filtering luma and chromacomponents independent from each other based on the number of presetsfor the chroma component in one frame, and the number of presets for theluma component in the one frame.

The method may include, when luma and chroma components have differentpartitioning or semi-decoupled partitioning, perform the separateConstrained Directional Enhancement Filter (CDEF) process of filteringluma and chroma components independent from each other; and obtaining anoutput of the separate CDEF process that includes the filteredreconstructed samples of luma/chroma components, wherein an input of theseparate CDEF process is reconstructed samples of luma/chromacomponents, an intermediate output of the separate CDEF process includesusing the derived filter presets and a per-block level preset index.

The number of presets derived for the luma component is different fromthe number of presets derived for the chroma component at picture level.

The number of presets at picture level may include one of: 1, 2, 4, or8.

The number of presets derived and selected for the luma component in theone frame is 2, and the number of presets derived and selected for thechroma component in the one frame is 1.

The number of presets derived and selected for luma component is N,which is a positive integer, and the number of presets for chromacomponent is fixed as 1, which is derived as 1 in the decoder withoutsignaling.

The selected preset index for the current luma block is different from aselected preset index for the current chroma block, and an input of theseparate CDEF process is luma/chroma reconstructed samples of currentblock, and the presets derived and selected at frame level. The outputof this process is an index indicating which preset is selected forcurrent block.

The method may further comprise: when the number of the luma componentscorresponds to 8 presets and the number of the chroma componentcorresponds to 4 presets at frame level, select the preset index for aluma block A as 7, and the preset index for a chroma block B as 1,wherein the luma block A and the chroma block B are co-located orpartially co-located.

The method may further comprise: when deriving a CDEF filtering strengthof the chroma component, an input reconstructed sample is determined bycurrent chroma coded block size.

The method may further comprise: when current chroma block is of acertain size, an input is chroma reconstructed sample values of acurrent block having the certain size.

The method may further comprise: when separate partitioning or semide-coupled partitioning is applied to the luma and chroma blocks, lumaand chroma blocks still share the same preset index, and only one of theluma or chroma block size is employed in the preset indexderivation/signaling process.

The method may further comprise: when luma and chroma components havethe same coded block size, the CDEF filtering process of luma and chromacomponents are performed separately.

The picture level presets may be signaled separately for luma and chromacomponents in a high-level parameter set, slice header, picture header,or a Supplementary Enhancement Information (SEI) message.

The luma presets may be signaled first, then, chroma presets aresignaled.

The block level preset indexes are signaled separately for luma andchroma components.

The preset indexes of luma component are signaled first, then, presetindexes of chroma component are signaled.

A computer system for decoding video data may comprise: one or morecomputer-readable non-transitory storage media configured to storecomputer program code; and one or more computer processors configured toaccess said computer program code and operate as instructed by saidcomputer program code, said computer program code including: receivingcode configured to cause the one or more computer processors to receivevideo data comprising a chroma component and a luma component; parsing,deriving or selecting code configured to cause the one or more computerprocessors to parse, derive or select a number of presets for the chromacomponent in one frame, and a number of presets for the luma componentin the one frame; and decoding code configured to cause the one or morecomputer processors to decode the video data, wherein the methodcomprises performing a separate Constrained Directional EnhancementFilter (CDEF) process of filtering luma and chroma componentsindependent from each other based on the number of presets for thechroma component in one frame, and the number of presets for the lumacomponent in the one frame.

A non-transitory computer readable medium having stored thereon acomputer program for decoding video data may be configured to cause oneor more computer processors to: receive video data comprising a chromacomponent and a luma component; parse, derive or select code configuredto cause the one or more computer processors to parse, derive or selecta number of presets for the chroma component in one frame, and a numberof presets for the luma component in the one frame; and decode codeconfigured to cause the one or more computer processors to decode thevideo data, wherein the method comprises performing a separateConstrained Directional Enhancement Filter (CDEF) process of filteringluma and chroma components independent from each other based on thenumber of presets for the chroma component in one frame, and the numberof presets for the luma component in the one frame.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other objects, features and advantages will become apparentfrom the following detailed description of illustrative embodiments,which is to be read in connection with the accompanying drawings. Thevarious features of the drawings are not to scale as the illustrationsare for clarity in facilitating the understanding of one skilled in theart in conjunction with the detailed description. In the drawings:

FIG. 1 illustrates a networked computer environment according to atleast one embodiment;

FIG. 2 illustrates adaptive loop filter (ALF) filter shapes;

FIGS. 3A-3D illustrates subsampled positions for diagonal gradients;

FIG. 4 illustrates a modified block classification at virtualboundaries;

FIG. 5 illustrates a modified ALF filtering for luma component atvirtual boundaries;

FIG. 6 illustrates a location of chroma samples relative to lumasamples;

FIG. 7 illustrates an example of direction search for an 8×8 block;

FIG. 8 illustrates an example of direction search for an 8×8 block;

FIG. 9 illustrates an example of coding tree structures (luma andchroma);

FIG. 10 illustrates a Separate Constrained Directional EnhancementFilter (SCDEF);

FIG. 11 is an operational flowchart illustrating the steps carried outby a program that codes video data, according to at least oneembodiment;

FIG. 12 is a block diagram of internal and external components ofcomputers and servers depicted in FIG. 1 according to at least oneembodiment;

FIG. 13 is a block diagram of an illustrative cloud computingenvironment including the computer system depicted in FIG. 1, accordingto at least one embodiment; and

FIG. 14 is a block diagram of functional layers of the illustrativecloud computing environment of FIG. 13, according to at least oneembodiment.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. Those structures and methods may, however, beembodied in many different forms and should not be construed as limitedto the exemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the scope to those skilled in the art. Inthe description, details of well-known features and techniques may beomitted to avoid unnecessarily obscuring the presented embodiments.

Embodiments relate generally to the field of data processing, and moreparticularly to video encoding and/or decoding. The following describedexemplary embodiments provide a system, method and computer program to,among other things, encode and/or decode video data.

As previously described, AOMedia Video 1 (AV1) is an open video codingformat designed for video transmissions over the Internet. It wasdeveloped as a successor to VP9 by the Alliance for Open Media(AOMedia), a consortium founded in 2015 that includes semiconductorfirms, video on demand providers, video content producers, softwaredevelopment companies and web browser vendors.

Aspects are described herein with reference to flowchart illustrationsand/or block diagrams of methods, apparatus (systems), and computerreadable media according to the various embodiments. It will beunderstood that each block of the flowchart illustrations and/or blockdiagrams, and combinations of blocks in the flowchart illustrationsand/or block diagrams, can be implemented by computer readable programinstructions.

Referring now to FIG. 1, a functional block diagram of a networkedcomputer environment illustrating a video coding system 100 (hereinafter“system”) for encoding and/or decoding video data according to anembodiment. It should be appreciated that FIG. 1 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environments may be madebased on design and implementation requirements.

The system 100 may include a computer 102 and a server computer 114. Thecomputer 102 may communicate with the server computer 114 via acommunication network 110 (hereinafter “network”). The computer 102 mayinclude a processor 104 and a software program 108 that is stored on adata storage device 106 and is enabled to interface with a user andcommunicate with the server computer 114. As will be discussed belowwith reference to FIG. 12 the computer 102 may include internalcomponents 800A and external components 900A, respectively, and theserver computer 114 may include internal components 800B and externalcomponents 900B, respectively. The computer 102 may be, for example, amobile device, a telephone, a personal digital assistant, a netbook, alaptop computer, a tablet computer, a desktop computer, or any type ofcomputing devices capable of running a program, accessing a network, andaccessing a database.

The server computer 114 may also operate in a cloud computing servicemodel, such as Software as a Service (SaaS), Platform as a Service(PaaS), or Infrastructure as a Service (laaS), as discussed below withrespect to FIGS. 13 and 14. The server computer 114 may also be locatedin a cloud computing deployment model, such as a private cloud,community cloud, public cloud, or hybrid cloud.

The server computer 114, which may be used for encoding video data isenabled to run a Video Encoding or Decoding Program 116 (hereinafter“program”) that may interact with a database 112. The Video Encoding orDecoding Program method is explained in more detail below with respectto FIG. 3. In one embodiment, the computer 102 may operate as an inputdevice including a user interface while the program 116 may runprimarily on server computer 114. In an alternative embodiment, theprogram 116 may run primarily on one or more computers 102 while theserver computer 114 may be used for processing and storage of data usedby the program 116. It should be noted that the program 116 may be astandalone program or may be integrated into a larger video encodingprogram. The Video Encoding or Decoding Program 116 may be correspondingto an encoder, a decoder, or a coded (both encoder and decoder).

It should be noted, however, that processing for the program 116 may, insome instances be shared amongst the computers 102 and the servercomputers 114 in any ratio. In another embodiment, the program 116 mayoperate on more than one computer, server computer, or some combinationof computers and server computers, for example, a plurality of computers102 communicating across the network 110 with a single server computer114. In another embodiment, for example, the program 116 may operate ona plurality of server computers 114 communicating across the network 110with a plurality of client computers. Alternatively, the program mayoperate on a network server communicating across the network with aserver and a plurality of client computers.

The network 110 may include wired connections, wireless connections,fiber optic connections, or some combination thereof. In general, thenetwork 110 can be any combination of connections and protocols thatwill support communications between the computer 102 and the servercomputer 114. The network 110 may include various types of networks,such as, for example, a local area network (LAN), a wide area network(WAN) such as the Internet, a telecommunication network such as thePublic Switched Telephone Network (PSTN), a wireless network, a publicswitched network, a satellite network, a cellular network (e.g., a fifthgeneration (5G) network, a long-term evolution (LTE) network, a thirdgeneration (3G) network, a code division multiple access (CDMA) network,etc.), a public land mobile network (PLMN), a metropolitan area network(MAN), a private network, an ad hoc network, an intranet, a fiberoptic-based network, or the like, and/or a combination of these or othertypes of networks.

The number and arrangement of devices and networks shown in FIG. 1 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 1. Furthermore, two or more devices shown in FIG. 1 may beimplemented within a single device, or a single device shown in FIG. 1may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) of system100 may perform one or more functions described as being performed byanother set. of devices of system 100.

1 Adaptive Loop Filter (ALF)

In Versatile Video Coding (VVC) (Draft 8), an Adaptive Loop Filter (ALF)with block-based filter adaption is applied. For the luma component, oneamong 25 filters is selected for each 4×4 block, based on the directionand activity of local gradients.

1.1 Filter Shape

In VVC (Draft 8), two diamond filter shapes (as shown in FIG. 2) may beused. The 7×7 diamond shape is applied for luma component and the 5×5diamond shape is applied for chroma components.

1.2 Block Classification

For luma component, each 4×4 block is categorized into one out of 25classes. The classification index C is derived based on itsdirectionality D and a quantized value of activity A, as follows:C=5D+Â  (Eq. 1)

To calculate D and Â, gradients of the horizontal, vertical and twodiagonal direction are first calculated using 1-D Laplacian:g _(v)=Σ_(k=i-2) ^(i+3)Σ_(l=j-2) ^(j+3) V _(k,l) V_(k,l)=|2R(k,l)−R(k,l−1)−R(k,l+1)|  (Eq. 2)g _(h)=Σ_(k=i-2) ^(i+3)Σ_(l=j-2) ^(j+3) H _(k,l) H_(k,l)|2R(k,l)−R(k−1,l)−R(k+1,l)|  (Eq. 3)g _(d1)=Σ_(k=i-2) ^(i+3)Σ_(l=j-3) ^(j+3) D1_(k,l),D1_(k,l)=|2R(k,l)−R(k−1,l−1)−R(k+1,l+1)|   (Eq. 4)g _(d2)=Σ_(k=i-2) ^(i+3)Σ_(j=j-2) ^(j+3) D1_(k,l),D1_(k,l)=|2R(k,l)−R(k−1,l−1)−R(k+1,l+1)|   (Eq. 5)

Where indices i and j refer to the coordinates of the upper left samplewithin the 4×4 block and R(i,j) indicates a reconstructed sample atcoordinate (i,j).

To reduce the complexity of block classification, the subsampled 1-DLaplacian calculation is applied. As shown in FIGS. 3A-3D, the samesubsampled positions are used for gradient calculation of all directions(e.g., a subsampled Laplacian calculation for all directions). Forexample, FIG. 3A shows subsampled positions for vertical gradient, FIG.3B shows subsampled positions for horizontal gradient, and FIGS. 3C and3D show subsampled portions for diagonal gradients.

Then D maximum and minimum values of the gradients of horizontal andvertical directions are set as:g _(h,v) ^(max)=max(g _(h) ,g _(v)),g _(h,v) ^(min)=min(g _(h) ,g_(v))  (Eq. 6)

The maximum and minimum values of the gradient of two diagonaldirections are set as:g= _(d1,d2) ^(max)=max(g _(d1) ,g _(d2)),g _(d1,d2) ^(min)=min(g _(d1),g _(d2))  (Eq. 7)

To derive the value of the directionality D, these values are comparedagainst each other and with two thresholds t₁ and t₂:

Step 1. If both g_(h,v) ^(max)≤t₁·g_(h,v) ^(min) and g_(d1,d2)^(max)≤t₁·g_(d1,d2) ^(min) are true, D is set to 0.

Step 2. If g_(h,v) ^(max)/g_(h,v) ^(min)>g_(d1,d2) ^(max)/g_(d1,d2)^(min), continue from Step 3; otherwise continue from Step 4.

Step 3. If g_(h,v) ^(max)>t₂·g_(h,v) ^(min), D is set to 2; otherwise Dis set to 1.

Step 4. If g_(d1,d2) ^(max)>t₂·g_(d1,d2) ^(min), D is set to 4;otherwise D is set to 3.

The activity value A is calculated as:A=Σ _(k=i-2) ^(i+3)Σ_(l=j-2) ^(j+3)(V _(k,l) +H _(k,l))  (Eq. 8)

A is further quantized to the range of 0 to 4, inclusively, and thequantized value is denoted as Â.

For chroma components in a picture, no classification method is applied,i.e. a single set of ALF coefficients is applied for each chromacomponent.

1.3 Geometric Transformations of Filter Coefficients and Clipping Values

Before filtering each 4×4 luma block, geometric transformations such asrotation or diagonal and vertical flipping are applied to the filtercoefficients f(k,l) and to the corresponding filter clipping valuesc(k,l) depending on gradient values calculated for that block. This isequivalent to applying these transformations to the samples in thefilter support region. The idea is to make different blocks to which ALFis applied more similar by aligning their directionality.

Three geometric transformations, including diagonal, vertical flip androtation are introduced:Diagonal:f _(D)(k,l)=f(l,k),c _(D)(k,l)=(l,k),  (Eq. 9)Vertical flip:f _(V)(k,l)=f(k,K−l−1),c _(V)(k,l)=c(k,K−l−1)  (Eq. 10)Rotation:f _(R)(k,l)=f(K−l−1,k),c _(R)(k,l)=c(K−l−1,k)  (Eq. 11)

where K is the size of the filter and 0≤k,l≤K−1 are coefficientscoordinates, such that location (0,0) is at the upper left corner andlocation (K−1, K−1) is at the lower right corner. The transformationsare applied to the filter coefficients f(k,l) and to the clipping valuesc(k,l) depending on gradient values calculated for that block. Therelationship between the transformation and the four gradients of thefour directions are summarized in the following Table 1.

TABLE 1 Mapping of the gradient calculated for one block and thetransformations Gradient values Transformation g_(d2) < g_(d1) and g_(h)< g_(v) No transformation g_(d2) < g_(d1) and g_(v) < g_(h) Diagonalg_(d1) < g_(d2) and g_(h) < g_(v) Vertical flip g_(d1) < g_(d2) andg_(v) < g_(h) Rotation

1.4 Filter Parameters Signalling

In VVC (Draft 8), ALF filter parameters are signalled in adaptationparameter set (APS). In one APS, up to 25 sets of luma filtercoefficients and clipping value indexes, and up to eight sets of chromafilter coefficients and clipping value indexes could be signalled. Toreduce bits overhead, filter coefficients of different classificationfor luma component can be merged. In slice header, the indices of theAPSs used for the current slice are signaled. The signaling of ALF isCTU-based in VVC (Draft 8).

Clipping value indexes, which are decoded from the APS, allowdetermining clipping values using a table of clipping values for Lumaand Chroma. These clipping values are dependent of the internalbitdepth. More precisely, the table of clipping values is obtained bythe following formula:AlfClip={round(2^(B-α*n)) for n∈[0 . . . N−1]}  (Eq. 12)with B equal to the internal bitdepth, α is a pre-defined constant valueequal to 2.35, and N equal to 4 which is the number of allowed clippingvalues in VVC (Draft 8).

Table 2 shows the output of equation 12.

TABLE 2 Specification AlfClip depending on bitDepth and clipIdx clipIdxbitDepth 0 1 2 3 8 255 50 10 2 9 511 100 20 4 10 1023 201 39 8 11 2047402 79 15 12 4095 803 158 31 13 8191 1607 315 62 14 16383 3214 630 12415 32767 6427 1261 247 16 65535 12855 2521 495

In slice header, up to 7 APS indices can be signaled to specify the lumafilter sets that are used for the current slice. The filtering processcan be further controlled at coding tree block (CTB) level. A flag isalways signalled to indicate whether ALF is applied to a luma CTB. Aluma CTB can choose a filter set among 16 fixed filter sets and thefilter sets from APSs. A filter set index is signaled for a luma CTB toindicate which filter set is applied. The 16 fixed filter sets arepre-defined and hardcoded in both the encoder and the decoder.

For chroma component, an APS index is signaled in slice header toindicate the chroma filter sets being used for the current slice. At CTBlevel, a filter index is signaled for each chroma CTB if there is morethan one chroma filter set in the APS.

The filter coefficients may be quantized with norm equal to 128. Inorder to restrict the multiplication complexity, a bitstream conformanceis applied so that the coefficient value of the non-central positionshall be in the range of −27 to 27−1, inclusive. The central positioncoefficient is not signalled in the bitstream and is considered as equalto 128.

In VVC (Draft 8), the syntaxes and semantics of clipping index andvalues are defined as follows: alf_luma_clip_idx[sfldx][j] specifies theclipping index of the clipping value to use before multiplying by thej-th coefficient of the signalled luma filter indicated by sfldx. It isa requirement of bitstream conformance that the values ofalf_luma_clip_idx[sfldx][j] with sfldx=0 . . .alf_luma_num_filters_signalled_minus1 and j=0 . . . 11 shall be in therange of 0 to 3, inclusive.

The luma filter clipping values AlfClipL[adaptation_parameter_set_id]with elements AlfClipL[adaptation_parameter_set_id][filtIdx][j], withfiltIdx=0 . . . NumAlfFilters−1 and j=0 . . . 11 are derived asspecified in Table 2 depending on bitDepth set equal to BitDepthY andclipldx set equal to alf_luma_clip_idx[alf_luma_coeff_delta_idx[filtIdx]][j].

alf_chroma_clip_idx[altIdx][j] specifies the clipping index of theclipping value to use before multiplying by the j-th coefficient of thealternative chroma filter with index altIdx. It is a requirement ofbitstream conformance that the values of alf_chroma_clip_idx[altIdx][j]with altIdx=0 . . . alf_chroma_num_alt_filters_minus1, j=0 . . . 5 shallbe in the range of 0 to 3, inclusive.

The chroma filter clipping valuesAlfClipC[adaptation_parameter_set_id][altIdx] with elementsAlfClipC[adaptation_parameter_set_id][altIdx][j], with altIdx=0 . . .alf_chroma_num_alt_filters_minus1, j=0 . . . 5 are derived as specifiedin Table 2 depending on bitDepth set equal to BitDepthC and clipIdx setequal to alf_chroma_clip_idx[altIdx][j].

1.5 Filtering Process

At decoder side, when ALF is enabled for a CTB, each sample R(i,j)within the CU is filtered, resulting in sample value R′(i,j) as shownbelow,R′(i,j)=R(i,j)+((Σ_(k≠0)Σ_(l≠0)f(k,l)×K(R(i+k,j+l)−R(i,j)c(k,l))+64)>>7)   (Eq. 13)where f(k,l) denotes the decoded filter coefficients, K(x,y) is theclipping function and c(k,l) denotes the decoded clipping parameters.The variable k and l vary between

${- \frac{L}{2}}\mspace{14mu}{and}\mspace{14mu}\frac{L}{2}$where L denotes the filter length. The clipping function K(x,y)=min(y,max(−y, x)) which corresponds to the function Clip3 (−y, y, x). Byincorporating this clipping function, this loop filtering method becomesa non-linear process, known as Non-Linear ALF. The selected clippingvalues are coded in the “alf_data” syntax element by using a Golombencoding scheme corresponding to the index of the clipping value inTable 2. This encoding scheme is the same as the encoding scheme for thefilter index.

1.6 Virtual Boundary Filtering Process for Line Buffer Reduction

To reduce the line buffer requirement of ALF, modified blockclassification and filtering are employed for the samples nearhorizontal CTU boundaries. For this purpose, a virtual boundary may bedefined as a line by shifting the horizontal CTU boundary with “N”samples as shown in FIG. 4, with N equal to 4 for the Luma component and2 for the Chroma component.

Modified block classification is applied for the Luma component asdepicted in FIG. 4. For the 1D Laplacian gradient calculation of the 4×4block above the virtual boundary, only the samples above the virtualboundary are used. Similarly, for the 1D Laplacian gradient calculationof the 4×4 block below the virtual boundary, only the samples below thevirtual boundary are used. The quantization of activity value A isaccordingly scaled by taking into account the reduced number of samplesused in 1D Laplacian gradient calculation.

For filtering processing, symmetric padding operation at the virtualboundaries are used for both Luma and Chroma components. As shown inFIG. 5 (“Modified ALF filtering for Luma component at virtualboundaries), when the sample being filtered is located below the virtualboundary, the neighboring samples that are located above the virtualboundary are padded. Meanwhile, the corresponding samples at the othersides are also padded, symmetrically.

1.7 Largest Coding Unit (LCU)-Aligned Picture Quadtree Splitting

In order enhance coding efficiency, the coding unit synchronous picturequadtree-based adaptive loop filter is proposed in JCTVC-C143 [3]. Theluma picture is split into several multi-level quadtree partitions, andeach partition boundary is aligned to the boundaries of the largestcoding units (LCUs). Each partition has its own filtering process andthus be called as a filter unit (FU).

The 2-pass encoding flow is described as follows. At the first pass, thequadtree split pattern and the best filter of each FU are decided. Thefiltering distortions are estimated by FFDE during the decision process.According to the decided quadtree split pattern and the selected filtersof all FUs, the reconstructed picture is filtered. At the second pass,the CU synchronous ALF on/off control is performed. According to the ALFon/off results, the first filtered picture is partially recovered by thereconstructed picture.

A top-down splitting strategy is adopted to divide a picture intomulti-level quadtree partitions by using a rate-distortion criterion.Each partition is called a filter unit. The splitting process alignsquadtree partitions with LCU boundaries. The encoding order of FUsfollows the z-scan order. For example, the picture may be split into 10FUs, and the encoding order is FU0, FU1, FU2, FU3, FU4, FU5, FU6, FU7,FU8, and FU9.

To indicate the picture quadtree split pattern, split flags may beencoded and transmitted in z-order.

The filter of each FU may be selected from two filter sets based on therate-distortion criterion. The first set may have ½-symmetricsquare-shaped and rhombus-shaped filters newly derived for the currentFU. The second set may come from time-delayed filter buffers; thetime-delayed filter buffers store the filters previously derived for FUsof prior pictures. The filter with the minimum rate-distortion cost ofthese two sets may be chosen for the current FU. Similarly, if thecurrent FU is not the smallest FU and can be further split into 4children FUs, the rate-distortion costs of the 4 children FUs arecalculated. By comparing the rate-distortion cost of the split andnon-split cases recursively, the picture quadtree split pattern can bedecided.

The maximum quadtree split level is 2 in JCTVC-C143, which means themaximum number of FUs is 16. During the quadtree split decision, thecorrelation values for deriving Wiener coefficients of the 16 FUs at thebottom quadtree level (smallest FUs) can be reused. The rest FUs canderive their Wiener filters from the correlations of the 16FUs at thebottom quadtree level. Therefore, there is only one frame buffer accessfor deriving the filter coefficients of all FUs.

After the quadtree split pattern is decided, to further reduce thefiltering distortion, the CU synchronous ALF on/off control isperformed. By comparing the filtering distortion and non-filteringdistortion, the leaf CU can explicitly switch ALF on/off in its localregion. The coding efficiency may be further improved by redesigning thefilter coefficients according to the ALF on/off results. However, theredesigning process needs additional frame buffer accesses. In theproposed CS-PQALF encoder design, there is no redesign process after theCU synchronous ALF on/off decision in order to minimize the number offrame buffer accesses.

2. Cross-Component Adaptive Loop Filter

Cross-component adaptive loop filter (CC-ALF) makes use of luma samplevalues to refine each chroma component.

CC-ALF operates by applying a linear, diamond shaped filter to the lumachannel for each chroma component. The filter coefficients aretransmitted in the APS, scaled by a factor of 2¹⁰, and rounded for fixedpoint representation. The application of the filters is controlled on avariable block size and signalled by a context-coded flag received foreach block of samples. The block size along with an CC-ALF enabling flagis received at the slice-level for each chroma component. In thecontribution the following block sizes (in chroma samples) weresupported 16×16, 32×32, 64×64.

Syntax changes of CC-ALF are described below in Table 3.

TABLE 3 if ( slice_cross_component_alf_cb_enabled_flag )alf_ctb_cross_component_cb_idc[ xCtb >> CtbLog2SizeY ][ yCtb >> CtbLae(v) og2SizeY ] if( slice_cross_component_alf_cb_enabled_flag = = 0 ||alf_ctb_cross_compo nent_cb_idc[ xCtb >> CtbLog2SizeY ][ yCtb >>CtbLog2SizeY ] == 0 ) if( slice_alf_chroma_idc = = 1 | |slice_alf_chroma_idc = = 3 ) { alf_ctb_flag[ 1 ][ xCtb >> CtbLog2SizeY][ yCtb >> CtbLog2SizeY ] ae(v) if( alf_ctb_flag[ 1 ][ xCtb >>CtbLog2SizeY ][ yCtb >> CtbLog2SizeY ] &&aps_alf_chroma_num_alt_filters_minus1 > 0 ) alf_ctb_filter_alt_idx[ 0 ][xCtb >> CtbLog2SizeY ][ yCtb >> CtbLog2Size ae(v) Y ] } if (slice_cross_component_alf_cr_enabled_flag )alf_ctb_cross_component_cr_idc[ xCtb >> CtbLog2SizeY ][ yCtb >> CtbLae(v) og2SizeY ] if( slice_cross_component_alf_cr_enabled_flag = = 0 ||alf_ctb_cross_compo nent_cr_idc[ xCtb >> CtbLog2SizeY ][ yCtb >>CtbLog2SizeY ] == 0 ) if( slice_alf_chroma_idc = = 2 | |slice_alf_chroma_idc = = 3 ) { alf_ctb_flag[ 2 ][ xCtb >> CtbLog2SizeY][ yCtb >> CtbLog2SizeY ] ae(v) if( alf_ctb_flag[ 2 ][ xCtb >>CtbLog2SizeY ][ yCtb >> CtbLog2SizeY ] &&aps_alf_chroma_num_alt_filters_minus1 > 0 ) alf_ctb_filter_alt_idx[ 1 ][xCtb >> CtbLog2SizeY ][ yCtb >> CtbLog2Size ae(v) Y ] }

The semantics of CC-ALF related syntaxes are described below:

alf_ctb_cross_component_cb_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2Size Y]equal to 0 indicates that the cross component Cb filter is not appliedto block of Cb colour component samples at luma location (xCtb, yCtb).

alf_cross_component_cb_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY] notequal to 0 indicates that thealf_cross_component_cb_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]-thcross component Cb filter is applied to the block of Cb colour componentsamples at luma location (xCtb, yCtb)

alf_ctb_cross_component_cr_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2Size Y]equal to 0 indicates that the cross component Cr filter is not appliedto block of Cr colour component samples at luma location (xCtb, yCtb).alf_cross_component_cr_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY] notequal to 0 indicates that thealf_cross_component_cr_idc[xCtb>>CtbLog2SizeY][yCtb>>CtbLog2SizeY]-thcross component Cr filter is applied to the block of Cr colour componentsamples at luma location (xCtb, yCtb)

3 Chroma Sampling Formats

FIG. 6 (“Location of chroma samples relative to luma samples”) of thepresent application illustrates the indicated relative position of thetop-left chroma sample when chroma_format_idc is equal to 1 (4:2:0chroma format), and chroma_sample_loc_type_top_field orchroma_sample_loc_type_bottom field is equal to the value of a variableChromaLocType. The region represented by the top-left 4:2:0 chromasample (depicted as a large red square with a large red dot at itscentre) is shown relative to the region represented by the top-left lumasample (depicted as a small black square with a small black dot at itscentre). The regions represented by neighbouring luma samples aredepicted as small grey squares with small grey dots at their centres.

4 Constrained Directional Enhancement Filter

The main goal of the in-loop constrained directional enhancement filter(CDEF) is to filter out coding artifacts while retaining the details ofthe image. In HEVC, the Sample Adaptive Offset (SAO) algorithm achievesa similar goal by defining signal offsets for different classes ofpixels. Unlike SAO, CDEF is a non-linear spatial filter. The design ofthe filter has been constrained to be easily vectorizable (i.e.implementable with SIMD operations), which was not the case for othernon-linear filters like the median filter and the bilateral filter.

The CDEF design originates from the following observations. The amountof ringing artifacts in a coded image tends to be roughly proportionalto the quantization step size. The amount of detail is a property of aninput image, but the smallest detail retained in the quantized imagetends to also be proportional to the quantization step size. For a givenquantization step size, the amplitude of the ringing is generally lessthan the amplitude of the details.

CDEF works by identifying the direction of each block and thenadaptively filtering along the identified direction and to a lesserdegree along directions rotated 45 degrees from the identifieddirection. The filter strengths are signaled explicitly, which allows ahigh degree of control over the blurring. An efficient encoder search isdesigned for the filter strengths. CDEF is based on two previouslyproposed in-loop filters and the combined filter was adopted for theemerging AV1 codec.

4.1 Direction Search

The direction search operates on the reconstructed pixels, just afterthe deblocking filter. Since those pixels are available to the decoder,the directions require no signaling. The search operates on 8×8 blocks,which are small enough to adequately handle non-straight edges, whilebeing large enough to reliably estimate directions when applied to aquantized image. Having a constant direction over an 8×8 region alsomakes vectorization of the filter easier. For each block we determinethe direction that best matches the pattern in the block by minimizingthe sum of squared differences (SSD) between the quantized block and theclosest perfectly directional block. A perfectly directional block is ablock where all of the pixels along a line in one direction have thesame value. FIG. 7 is an example of direction search for an 8×8 block.In this case, the 45-degree direction (as shown by the box around column12) is selected because it minimizes the error.

4.2 Non-linear low-pass directional filter

The main reason for identifying the direction is to align the filtertaps along that direction to reduce ringing while preserving thedirectional edges or patterns. However, directional filtering alonesometimes cannot sufficiently reduce ringing. It is also desired to usefilter taps on pixels that do not lie along the main direction. Toreduce the risk of blurring, these extra taps are treated moreconservatively. For this reason, CDEF defines primary taps and secondarytaps. The complete 2-D CDEF filter is expressed as

$\begin{matrix}{{{y( {i,j} )} = {{x( {i,j} )} + {{round}( {{\sum\limits_{m,n}{w_{d,m,n}^{(p)}{f( {{{x( {m,n} )} - {x( {i,j} )}},S^{(p)},D} )}}} + {\sum\limits_{m,n}{w_{d,m,n}^{(s)}{f( {{{x( {m,n} )} - {x( {i,j} )}},S^{(s)},D} )}}}} )}}},} & ( {{Eq}.\mspace{14mu} 14} )\end{matrix}$where D is the damping parameter, S^((p)) and S^((s)) are the strengthsof the primary and secondary taps, respectively, and round(·) roundsties away from zero, w_(k) are the filter weights and f(d, S, D) is aconstraint function operating on the difference between the filteredpixel and each of the neighboring pixels. For small differences, f(d, S,D)=d, making the filter behave like a linear filter. When the differenceis large, f(d, S, D)=0, which effectively ignores the filter tap.

5. Loop Restoration in AV1

A set of in-loop restoration schemes are proposed for use in videocoding post deblocking, to generally denoise and enhance the quality ofedges, beyond the traditional deblocking operation. These schemes areswitchable within a frame per suitably sized tile. The specific schemesdescribed are based on separable symmetric Wiener filters and dualself-guided filters with subspace projection. Because content statisticscan vary substantially within a frame, these tools are integrated withina switchable framework where different tools can be triggered indifferent regions of the frame.

5.1 Separable Symmetric Wiener Filter

One restoration tool that has been shown to be promising in theliterature is the Wiener filter. Every pixel in a degraded frame couldbe reconstructed as a non-causal filtered version of the pixels within aw×w window around it where w=2r+1 is odd for integer r. If the 2D filtertaps are denoted by a w²×1 element vector F in column-vectorized form, astraightforward LMMSE optimization leads to filter parameters beinggiven by F=H⁻¹ M, where H=E[XX^(T)] is the autocovariance of x, thecolumn-vectorized version of the w² samples in the w×w window around apixel, and M=E[YX^(T)] is the cross correlation of x with the scalarsource sample y, to be estimated. The encoder can estimate H and M fromrealizations in the deblocked frame and the source and send theresultant filter F to the decoder. However, that would not only incur asubstantial bit rate cost in transmitting w² taps, but alsonon-separable filtering will make decoding prohibitively complex.Therefore, several additional constraints are imposed on the nature ofF. First, F is constrained to be separable so that the filtering can beimplemented as separable horizontal and vertical w-tap convolutions.Second, each of the horizontal and vertical filters are constrained tobe symmetric. Third, the sum of both the horizontal and vertical filtercoefficients is assumed to sum to 1.

5.2 Dual Self-Guided Filtering with Subspace Projection

Guided filtering is one of the more recent paradigms of image filteringwhere a local linear model:y=Fx+G  (Eq. 15)is used to compute the filtered output y from an unfiltered sample x,where F and G are determined based on the statistics of the degradedimage and a guidance image in the neighborhood of the filtered pixel. Ifthe guide image is the same as the degraded image, the resultantso-called self-guided filtering has the effect of edge preservingsmoothing. The specific form of self-guided filtering we propose dependson two parameters: a radius r and a noise parameter e, and is enumeratedas follows:

-   -   1. Obtain mean μ and variance σ² of pixels in a (2r+1)×(2r+1)        window around every pixel. This can be implemented efficiently        with box filtering based on integral imaging.    -   2. Compute for every pixel: f=σ²(σ²+e); g=(1−f)μ    -   3. Compute F and G for every pixel as averages off and g values        in a 3×3 window around the pixel for use.

Filtering is controlled by r and e, where a higher r implies a higherspatial variance and a higher e implies a higher range variance.

The principle of subspace projection is illustrated diagrammatically inFIG. 8. Even though none of the cheap restorations X₁, X₂ are close tothe source Y, appropriate multipliers {α, β} can bring them much closerto the source as long as they are moving somewhat in the rightdirection. FIG. 8 shows a subspace projection using cheap restorationsto produce a final restoration closer to the source.

6. Semi Decoupled Partitioning

A semi decoupled partitioning (SDP) scheme, or a semi separate tree(SST) or flexible block partitioning for chroma component. In thismethod, luma and chroma block in one super block (SB) may have same ordifferent block partitioning, which is dependent on the luma coded blocksizes or the luma tree depth. To be specific, when the luma block areasize is greater than one threshold T1 or coding tree splitting depth ofluma block is smaller than or equal to one threshold T2, then chromablock uses the same coding tree structure as luma. Otherwise when theblock area size is smaller than or equal to T1 or luma splitting depthis larger than T2, the corresponding chroma block can have differentcoding block partitioning with luma component, which is called flexibleblock partitioning for chroma component. T1 is a positive integer, suchas 128 or 256. T2 is a positive integer, such as 1 or 2.

An improved semi decoupled partitioning (SDP) scheme was proposed,wherein luma and chroma component may share the partial tree structurefrom the root node of the super block, and the condition on when lumaand chroma start separate tree partitioning depends on partitioninginformation of luma. For example, FIG. 9 shows an example of the codingtree structure for luma and chroma component.

In Constrained Directional Enhancement Filter (CDEF), luma and chromacomponents are limited to share presets at picture level. Additionally,luma and chroma components are also limited to have the same presetindex at block level. Lastly, when deriving the filter strength ofchroma component, luma block size is used to determine an input ofchroma component. These constraints may limit the coding efficiency ofCDEF.

In traditional CDEF, one preset contains luma and chromaprimary/secondary strength. The number of allowed/available presets aresignaled at picture level. At coded block level, an index is signaled toindicate which preset is selected for current block. Coded block sizesof CDEF include 128×128, 128×64, 64×64, and 64×128. There are threelimitations of traditional CDEF: one limitation is that luma and chromacomponents are forced to share presets at picture level; anotherlimitation is that luma and chroma components are forced to pick thesame preset index at block level; one more limitation is that whenderiving the filter strength of chroma component, luma block size isused to determine an input of chroma component. The aforementionedlimitations together may limit the performance of CDEF, especially underthe situation when luma and chroma components have differentpartitioning scheme, such as the partitioning scheme in semi decoupledpartitioning (SDP).

In this document, a Separate Constrained Directional Enhancement Filter(SCDEF) is proposed which performs the CDEF process of luma and chromacomponents separately. Compared with traditional CDEF, SCDEF allows thefiltering of luma and chroma components independent from each other. Tobe more specific, luma and chroma components may have different numberof presets at picture level; Moreover, luma and chroma components mayselect different preset index at block level; When deriving the filterstrength of chroma component, chroma block size is used to determine aninput of chroma component.

It is proposed that when luma and chroma components have differentpartitioning or semi-decoupled partitioning, CDEF filtering process ofluma and chroma components are performed separately, as shown in FIG.12. An input of the CDEF filtering process is the reconstructed samplesof luma/chroma components. The intermediate output of this processincludes but not limited to the derived filter presets and per-blocklevel preset index as mentioned in the above proposed method. Theeventual output of this process is the filtered reconstructed samples ofluma/chroma components.

In one embodiment, the number of presets derived for luma and chromacomponent may be different from each other at picture level. An input ofthe CDEF filtering process is the reconstructed samples in luma/chromacomponent. The output of this process is the derived presets at picturelevel. Example number of presets at picture level include but notlimited to 1, 2, 4, 8.

In one example, the number of presets derived and selected for currentluma component in one frame is 2, and the number of presets derived andselected for current chroma component in this frame is 1.

In another example, the number of presets derived and selected for lumacomponent is N, N is a positive integer, such as 1, 2, 4, or 8, whereasthe number of presets for chroma component is fixed as 1. The number ofpresets for chroma component does not need to be signaled in thebitstream, and derived as 1 in the decoder.

For example, FIG. 10 shows a Separate Constrained DirectionalEnhancement Filter (SCDEF).

In one embodiment, the selected preset index for current luma and chromablock may be different from each other. An input of this process isluma/chroma reconstructed samples of current block, and the presetsderived and selected at frame level. The output of this process is anindex indicating which preset is selected for current block.

In one example, when luma component has 8 presets and chroma componenthas 4 presets at frame level, the preset index selected for luma block Ais 7, and the preset index selected for chroma block B is 1. Luma blockA and chroma block B are co-located or partially co-located.

In one embodiment, when deriving the CDEF filtering strength of chromacomponent, an input reconstructed sample is determined by current chromacoded block size.

In one example, when current chroma block is of size 32×64, an input ischroma reconstructed sample values of current 32×64 block.

In one embodiment, when separate partitioning or semi de-coupledpartitioning is applied to luma and chroma blocks, luma and chromablocks still share the same preset index, and only the luma (or chroma)block size is employed in the preset index derivation/signaling process.

In some embodiments, when luma and chroma components have the same codedblock size, the CDEF filtering process of luma and chroma components areperformed separately.

In some embodiments, the signaling of SCDEF are performed separately forluma and chroma components.

In one embodiment, picture level presets are signaled separately forluma and chroma components. These presets can be signaled in high-levelparameter set (DPS, VPS, SPS, PPS, APS), slice header, picture header,SEI message.

In one example, luma presets are signaled first, then, chroma presetsare signaled.

In one embodiment, block level preset indexes are signaled separatelyfor luma and chroma components.

In one example, preset indexes of luma component are signaled first,then, preset indexes of chroma component are signaled.

Referring now to FIG. 11, an operational flowchart illustrating thesteps of a method 300 for decoding video data is depicted. However, oneof ordinary skill can appreciate how the encoding process would workbased on FIG. 11. In some implementations, one or more process blocks ofFIG. 3 may be performed by the computer 102 (FIG. 1) and the servercomputer 114 (FIG. 1). In some implementations, one or more processblocks of FIG. 3 may be performed by another device or a group ofdevices separate from or including the computer 102 and the servercomputer 114.

At 302, the method 300 includes receiving video data comprising a chromacomponent and a luma component.

At 304, the method 300 includes parsing, deriving or selecting a numberof presets for the chroma component in one frame, and a number ofpresets for the luma component in the one frame.

At 306, the method 300 includes encoding and/or decoding the video data.

Operation 306 may be based on the number of presets for the chromacomponent in one frame, and the number of presets for the luma componentin the one frame.

The method may further comprise: performing a separate ConstrainedDirectional Enhancement Filter (CDEF) process of filtering luma andchroma components independent from each other based on the number ofpresets for the chroma component in one frame, and the number of presetsfor the luma component in the one frame.

It may be appreciated that FIG. 11 provides only an illustration of oneimplementation and does not imply any limitations with regard to howdifferent embodiments may be implemented. Many modifications to thedepicted environments may be made based on design and implementationrequirements.

FIG. 12 is a block diagram 400 of internal and external components ofcomputers depicted in FIG. 1 in accordance with an illustrativeembodiment. It should be appreciated that FIG. 4 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environments may be madebased on design and implementation requirements.

Computer 102 (FIG. 1) and server computer 114 (FIG. 1) may includerespective sets of internal components 800A,B and external components900A,B illustrated in FIG. 12. Each of the sets of internal components800 include one or more processors 820, one or more computer-readableRAMs 822 and one or more computer-readable ROMs 824 on one or more buses826, one or more operating systems 828, and one or morecomputer-readable tangible storage devices 830.

Processor 820 is implemented in hardware, firmware, or a combination ofhardware and software. Processor 820 is a central processing unit (CPU),a graphics processing unit (GPU), an accelerated processing unit (APU),a microprocessor, a microcontroller, a digital signal processor (DSP), afield-programmable gate array (FPGA), an application-specific integratedcircuit (ASIC), or another type of processing component. In someimplementations, processor 820 includes one or more processors capableof being programmed to perform a function. Bus 826 includes a componentthat permits communication among the internal components 800A,B.

The one or more operating systems 828, the software program 108 (FIG. 1)and the Video Encoding Program 116 (FIG. 1) on server computer 114(FIG. 1) are stored on one or more of the respective computer-readabletangible storage devices 830 for execution by one or more of therespective processors 820 via one or more of the respective RAMs 822(which typically include cache memory). In the embodiment illustrated inFIG. 12, each of the computer-readable tangible storage devices 830 is amagnetic disk storage device of an internal hard drive. Alternatively,each of the computer-readable tangible storage devices 830 is asemiconductor storage device such as ROM 824, EPROM, flash memory, anoptical disk, a magneto-optic disk, a solid state disk, a compact disc(CD), a digital versatile disc (DVD), a floppy disk, a cartridge, amagnetic tape, and/or another type of non-transitory computer-readabletangible storage device that can store a computer program and digitalinformation.

Each set of internal components 800A,B also includes a R/W drive orinterface 832 to read from and write to one or more portablecomputer-readable tangible storage devices 936 such as a CD-ROM, DVD,memory stick, magnetic tape, magnetic disk, optical disk orsemiconductor storage device. A software program, such as the softwareprogram 108 (FIG. 1) and the Video Encoding Program 116 (FIG. 1) can bestored on one or more of the respective portable computer-readabletangible storage devices 936, read via the respective R/W drive orinterface 832 and loaded into the respective hard drive 830.

Each set of internal components 800A,B also includes network adapters orinterfaces 836 such as a TCP/IP adapter cards; wireless Wi-Fi interfacecards; or 3G, 4G, or 5G wireless interface cards or other wired orwireless communication links. The software program 108 (FIG. 1) and theVideo Encoding Program 116 (FIG. 1) on the server computer 114 (FIG. 1)can be downloaded to the computer 102 (FIG. 1) and server computer 114from an external computer via a network (for example, the Internet, alocal area network or other, wide area network) and respective networkadapters or interfaces 836. From the network adapters or interfaces 836,the software program 108 and the Video Encoding Program 116 on theserver computer 114 are loaded into the respective hard drive 830. Thenetwork may comprise copper wires, optical fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers.

Each of the sets of external components 900A,B can include a computerdisplay monitor 920, a keyboard 930, and a computer mouse 934. Externalcomponents 900A,B can also include touch screens, virtual keyboards,touch pads, pointing devices, and other human interface devices. Each ofthe sets of internal components 800A,B also includes device drivers 840to interface to computer display monitor 920, keyboard 930 and computermouse 934. The device drivers 840, R/W drive or interface 832 andnetwork adapter or interface 836 comprise hardware and software (storedin storage device 830 and/or ROM 824).

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,some embodiments are capable of being implemented in conjunction withany other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (laaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring to FIG. 13, illustrative cloud computing environment 500 isdepicted. As shown, cloud computing environment 500 comprises one ormore cloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Cloud computingnodes 10 may communicate with one another. They may be grouped (notshown) physically or virtually, in one or more networks, such asPrivate, Community, Public, or Hybrid clouds as described hereinabove,or a combination thereof. This allows cloud computing environment 600 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 13 are intended to be illustrative only and that cloud computingnodes 10 and cloud computing environment 500 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring to FIG. 14, a set of functional abstraction layers 600provided by cloud computing environment 500 (FIG. 13) is shown. Itshould be understood in advance that the components, layers, andfunctions shown in FIG. 6 are intended to be illustrative only andembodiments are not limited thereto. As depicted, the following layersand corresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and Video Encoding/Decoding 96.

Some embodiments may relate to a system, a method, and/or a computerreadable medium at any possible technical detail level of integration.The computer readable medium may include a computer-readablenon-transitory storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outoperations.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program code/instructions for carrying out operationsmay be assembler instructions, instruction-set-architecture (ISA)instructions, machine instructions, machine dependent instructions,microcode, firmware instructions, state-setting data, configuration datafor integrated circuitry, or either source code or object code writtenin any combination of one or more programming languages, including anobject oriented programming language such as Smalltalk, C++, or thelike, and procedural programming languages, such as the “C” programminglanguage or similar programming languages. The computer readable programinstructions may execute entirely on the user's computer, partly on theuser's computer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider). In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) may execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects or operations.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer readable media according to variousembodiments. In this regard, each block in the flowchart or blockdiagrams may represent a module, segment, or portion of instructions,which comprises one or more executable instructions for implementing thespecified logical function(s). The method, computer system, and computerreadable medium may include additional blocks, fewer blocks, differentblocks, or differently arranged blocks than those depicted in theFigures. In some alternative implementations, the functions noted in theblocks may occur out of the order noted in the Figures. For example, twoblocks shown in succession may, in fact, be executed concurrently orsubstantially concurrently, or the blocks may sometimes be executed inthe reverse order, depending upon the functionality involved. It willalso be noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

It will be apparent that systems and/or methods, described herein, maybe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwaremay be designed to implement the systems and/or methods based on thedescription herein.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and may be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

The descriptions of the various aspects and embodiments have beenpresented for purposes of illustration, but are not intended to beexhaustive or limited to the embodiments disclosed. Even thoughcombinations of features are recited in the claims and/or disclosed inthe specification, these combinations are not intended to limit thedisclosure of possible implementations. In fact, many of these featuresmay be combined in ways not specifically recited in the claims and/ordisclosed in the specification. Although each dependent claim listedbelow may directly depend on only one claim, the disclosure of possibleimplementations includes each dependent claim in combination with everyother claim in the claim set. Many modifications and variations will beapparent to those of ordinary skill in the art without departing fromthe scope of the described embodiments. The terminology used herein waschosen to best explain the principles of the embodiments, the practicalapplication or technical improvement over technologies found in themarketplace, or to enable others of ordinary skill in the art tounderstand the embodiments disclosed herein.

Acronyms used throughout the disclosure include the following:

-   HEVC: High Efficiency Video Coding-   HDR: high dynamic range-   SDR: standard dynamic range-   VVC: Versatile Video Coding-   JVET: Joint Video Exploration Team-   MPM: most probable mode-   WAIP: Wide-Angle Intra Prediction-   CU: Coding Unit-   CTB: Coding Tree Block-   PU: Prediction Unit-   TU: Transform Unit-   CTU: Coding Tree Unit-   PDPC: Position Dependent Prediction Combination-   ISP: Intra Sub-Partitions-   SPS: Sequence Parameter Setting-   PPS: Picture Parameter Set-   APS: Adaptation Parameter Set-   VPS: Video Parameter Set-   DPS: Decoding Parameter Set-   ALF: Adaptive Loop Filter-   SAO: Sample Adaptive Offset-   CC-ALF: Cross-Component Adaptive Loop Filter-   CDEF: Constrained Directional Enhancement Filter-   LR: Loop Restoration Filter-   AV1: AOMedia Video 1-   AV2: AOMedia Video 2-   SDP: Semi Decoupled Partitioning-   SEI: Supplementary Enhancement Information

What is claimed is:
 1. A method of video decoding, executable by aprocessor, the method comprising: receiving video data comprising achroma component and a luma component; parsing, deriving or selecting anumber of presets for the chroma component in one frame, and a number ofpresets for the luma component in the one frame; decoding the videodata; and performing a first Constrained Directional Enhancement Filter(CDEF) process of filtering luma based on the number of presets for theluma component in the one frame, and performing a second CDEF processchroma components, which is separate and independent from the first CDEFprocess, based on the number of presets for the chroma component in theone frame, wherein the number of presets for the luma component aredifferent from the number of presets for the chroma component, whereinthe number of presets derived for the luma component are different fromthe number of presets derived for the chroma component at picture level,and wherein the number of presets at picture level include one of: 1, 2,4, or
 8. 2. The method of claim 1, further comprising: when luma andchroma components have different partitioning or semi-decoupledpartitioning, performing the first and second CDEF processes offiltering luma and chroma components; and obtaining an output of thefirst and second CDEF processes that includes filtered reconstructedsamples of respective luma/chroma components, wherein an input of thefirst and second CDEF processes is reconstructed samples of therespective luma/chroma components, an intermediate output of the firstand second CDEF processes includes derived filter presets and aper-block level preset index.
 3. The method of claim 1, wherein thenumber of presets derived and selected for the luma component in the oneframe is 2, and the number of presets derived and selected for thechroma component in the one frame is
 1. 4. The method of claim 1,wherein the number of presets derived and selected for the lumacomponent is N, which is a positive integer, and the number of presetsfor the chroma component is fixed as 1, which is derived as 1 in adecoder without signaling.
 5. The method of claim 1, wherein a selectedpreset index for a current luma block is different from a selectedpreset index for a current chroma block, an input of the first andsecond CDEF processes is respective luma/chroma reconstructed samples ofthe current respective luma/chroma block(s), and the presets derived andselected at frame level, and an output of the first and second CDEFprocesses is an index indicating which preset is selected for thecurrent respective luma/chroma block(s).
 6. The method of claim 1,further comprising: when the number of presets for the luma componentcorresponds to 8 presets and the number of presets for the chromacomponent corresponds to 4 presets at frame level, selecting a presetindex for a luma block A as 7, and selecting a preset index for a chromablock B as 1, wherein the luma block A and the chroma block B areco-located or partially co-located.
 7. The method of claim 1, wherein,when deriving a CDEF filtering strength of the chroma component, aninput reconstructed sample is determined by current chroma coded blocksize.
 8. The method of claim 7, wherein, when current chroma block is ofa certain size, an input is chroma reconstructed sample values of acurrent block having the certain size.
 9. The method of claim 1,wherein, when separate partitioning or semi de-coupled partitioning isapplied to the luma and chroma blocks, luma and chroma blocks stillshare the same preset index, and only one of the luma or chroma blocksize is employed in the preset index derivation.
 10. The method of claim1, wherein, when luma and chroma components have the same coded blocksize, the CDEF filtering process of luma and chroma components areperformed separately.
 11. The method of claim 1, wherein picture levelpresets are signaled separately for the luma component and the chromacomponent in a high level parameter set, slice header, picture header,or a Supplementary Enhancement Information (SEI) message.
 12. The methodof claim 11, wherein luma presets are signaled first, and then chromapresets are signaled.
 13. The method of claim 1, wherein block levelpreset indexes are signaled separately for luma and chroma components.14. The method of claim 13, wherein preset indexes of the lumacomponents are signaled first, and then preset indexes of the chromacomponent are signaled.
 15. A computer system for decoding video data,the computer system comprising: one or more computer-readablenon-transitory storage media configured to store computer program code;and one or more computer processors configured to access said computerprogram code and operate as instructed by said computer program code,said computer program code including: receiving code configured to causethe one or more computer processors to receive video data comprising achroma component and a luma component; parsing, deriving or selectingcode configured to cause the one or more computer processors to parse,derive or select a number of presets for the chroma component in oneframe, and a number of presets for the luma component in the one frame;decoding code configured to cause the one or more computer processors todecode the video data; and performing code configured to cause the oneor more computer processors to perform a first Constrained DirectionalEnhancement Filter (CDEF) process of filtering luma based on the numberof presets for the luma component in the one frame, and perform a secondCDEF process chroma components, which is separate and independent fromthe first CDEF process, based on the number of presets for the chromacomponent in the one frame, wherein the number of presets for the lumacomponent are different from the number of presets for the chromacomponent, wherein the number of presets derived for the luma componentare different from the number of presets derived for the chromacomponent at picture level, and wherein the number of presets at picturelevel include one of: 1, 2, 4, or
 8. 16. A non-transitory computerreadable medium having stored thereon a computer program for decodingvideo data, the computer program configured to cause one or morecomputer processors to: receive video data comprising a chroma componentand a luma component; parse, derive or select code configured to causethe one or more computer processors to parse, derive or select a numberof presets for the chroma component in one frame, and a number ofpresets for the luma component in the one frame; decode code configuredto cause the one or more computer processors to decode the video data;and perform a first Constrained Directional Enhancement Filter (CDEF)process of filtering luma based on the number of presets for the lumacomponent in the one frame, and perform a second CDEF process chromacomponents, which is separate and independent from the first CDEFprocess, based on the number of presets for the chroma component in theone frame, wherein the number of presets for the luma component aredifferent from the number of presets for the chroma component, whereinthe number of presets derived for the luma component are different fromthe number of presets derived for the chroma component at picture level,and wherein the number of presets at picture level include one of: 1, 2,4, or 8.